make.sample.correlations.heatmap: Make a heatmap of the inter-sample correlations

In uclahs-cds/public-R-NanoStringNormCNV: Helper Functions to Normalize NanoString CNV Data

Make a heatmap of the inter-sample correlations

Description

Make a heatmap of inter-sample correlations of code counts

Usage

make.sample.correlations.heatmap(
  nano.counts, cor.method = 'pearson', fname.stem = NULL, covs = NULL
  )

Arguments

nano.counts	A gene by sample matrix or data-frame of NanoString counts, where row names are probe names and column names are sample IDs. Counts can be normalized or raw.
cor.method	Which distance method to use for clustering. Accepts 'pearson' (default), 'kendall', or 'spearman'
fname.stem	To use in filename. Description of how CNAs were called is suggested. Defaults to NULL
covs	A sample by covariate data-frame. Currently only accepts sample covariates 'Type' and 'Cartridge' (see output of load.phenodata). A 'SampleID' column is mandatory to match to 'nano.counts' sample IDs. Defaults to NULL

Details

Make a clustered heatmap of code count correlations for all samples

Value

None

Author(s)

Cindy Yao and Emilie Lalonde

Examples

## Not run: 
  # load data
  data(NanoString.DNA.raw);
  data(PhenoData);

	# make sure raw count data frame has gene names for rownames!
	NanoString.DNA.formatted <- NanoString.DNA.raw[, -(1:3)];
	rownames(NanoString.DNA.formatted) <- NanoString.DNA.raw$Name;

	# plot raw NanoString count correlations
	make.sample.correlations.heatmap(
		nano.counts = NanoString.DNA.formatted,
		covs = PhenoData[, c('SampleID', 'Cartridge', 'Type')]
		);

## End(Not run)

uclahs-cds/public-R-NanoStringNormCNV documentation built on May 31, 2024, 9:09 p.m.